http://mlsp.cs.cmu.edu/courses/fall2009/
(ECE number: 18-797)
Instructor: Bhiksha Raj
| This course is an elective in LTI, MLD and ECE |
| Credits: | 12 |
| Timings: | 4.30-5.50pm, Tuesdays and Thursdays |
| Location: | Porter Hall 125C |
| Prerequisites: |
| Mandatory: Linear Algebra. Basic Probability Theory. |
| Recommended: Signal Processing. Machine Learning. |
| Also Recommended: 18-799 by Joy Zhang would be an excellent course to take in parallel. This is also being conducted this fall. |
| LIST Of PROJECTS |
Signal Processing is the science that deals with extraction of information from signals of various kinds. This has two distinct aspects -- characterization and categorization. Traditionally, signal characterization has been performed with mathematically-driven transforms, while categorization and classification are achieved using statistical tools.
Machine learning aims to design algorithms that learn about the state of the world directly from data.
A increasingly popular trend has been to develop and apply machine learning techniques to both aspects of signal processing, often blurring the distinction between the two.
This course discusses the use of machine learning techniques to process signals. We cover a variety of topics, from data driven approaches for characterization of signals such as audio including speech, images and video, and machine learning methods for a variety of speech and image processing problems.
The course will roughly follow the following outline.
There will be several guest lectures. These will be announced as dates are finalized.
Grading will be based on performance in course assignments and a final project.
Outline
| Class 1, 25 Aug 2009 | Introduction. Basics: Representing audio and image data. | Slides | Additional material | |
| Class 2, 27 Aug 2009 | Linear Algebra Refresher | Slides | Additional material | |
| Class 3, 1 Sep 2009 | Linear Algebra Refresher, Part II | Slides | Homework Problem | |
| Class 4, 3 Sep 2009 | DSP Refresher. Representing Sounds and Images. | Slides | Additional Material | |
| Class 5, 8 Sep 2009 | No class | |||
| Class 6, 10 Sep 2009 | No class | |||
| Class 7, 15 Sep 2009 | Eigen faces. Boosting. Face detection | Slides | Homework Problem | Homework Problem No 2. |
| Class 8, 17 Sep 2009 | Component Analysis (Guest Lecture, De la Torre) | Slides | ||
| Class 9, 22 Sep 2009 | Project Ideas (with Guests Speakers) | Slides | Eakta Jain's Slides | Avidan's Seamcarving video |
| Class 10, 24 Sep 2009 | Speech synthesis, voice transformations (Guest Lecture, Black) | Slides | ||
| Class 11, 29 Sep 2009 | Boosting, Face detection, Recaps. | Slides | Additional Material | |
| Class 12, 1 Oct 2009 | Independent Component Analysis (Guest Lecture, Smaragdis) | Slides Handout | ||
| Class 13, 6 Oct 2009 | Latent variabe decomposition of audio signals | Slides | Additional Material | |
| Class 14, 8 Oct 2009 | Musical Onset Detection and Applications (Guest Lecture, Dannenberg) | Slides | ||
| Class 15, 13 Oct 2009 | Overcomplete decompositions. Nearest-neighbor decomposition. Shift-invariant and transform invariant models. | Slides | ||
| Class 16, 15 Oct 2009 | Non-negative matrix factorization and its application to audio (Guest Lec., Virtanen) | Slides | ||
| Class 17, 20 Oct 2009 | Pitch estimation, voice distortion (Guest Lecture, Black) | Slides | ||
| Class 18, 22 Oct 2009 | Shift-invariant decompositions; audio denoising. | Slides | ||
| Class 19, 27 Oct 2009 | Music Identification (Guest Lecture, Sukthankar) | Slides | ||
| Class 20, 29 Oct 2009 | Advanced component analysis (Guest Lecture, De la Torre) | Slides | ||
| Class 21, 3 Nov 2009 | Iris recognition (Guest Lecture, Kumar) | Slides | ||
| Class 22, 5 Nov 2009 | Automatic Speech Recognition in an Hour. | Slides | ||
| Class 23, 10 Nov 2009 | Sparse and overcomplete representations | Slides | ||
| Class 24, 12 Nov 2009 | Compressive Sensing (Boufonos) | Slides | ||
| Class 25, 17 Nov 2009 | Microphone array processing | Slides | ||
| Class 26, 19 Nov 2009 | Array processing -- maximum likelihood techniques, tracking, audio-visual tracing. | Slides | ||
| Class 27, 24 Nov 2009 | Project presentations | Slides | ||
| Class 28, 1 Dec 2009 | Project presentations | Slides | ||
| Class 29, 3 Dec 2009 | Project presentations | Slides |
No comments:
Post a Comment